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检索条件"任意字段=International Conference on Field Programmable Logic and Applications"

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A Hardware-Oriented Dropout Algorithm for Efficient FPGA Implementation 24th

A Hardware-Oriented Dropout Algorithm for Efficient FPGA Imp...

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24th international conference on Neural Information Processing (ICONIP)

作者： Yeoh, Yoeng Jye Morie, Takashi Tamukoh, Hakaru Kyushu Inst Technol Grad Sch Life Sci & Syst Engn Kitakyushu Fukuoka Japan

ISBN: (纸本)9783319701363;9783319701356

This paper proposes a hardware oriented dropout algorithm for an efficient field-programmable gate array (FPGA) implementation. Dropout is a regularization technique, which is commonly used in neural networks such as multilayer perceptrons (MLPs), convolutional neural networks (CNNs), among others. To generate a dropout mask to randomly drop neurons during training phase, random number generators (RNGs) are usually used in software implementations. However, RNGs consume considerable FPGA resources in hardware implementations. The proposed method is able to minimize the resources required for FPGA implementation of dropout by performing a simple rotation operation to a predefined dropout mask. We apply the proposed method to MLPs and CNNs and evaluate them on MNIST and CIFAR-10 classification. In addition, we employ the proposed method in GoogLeNet training using own dataset to develop a vision system for home service robots. The experimental results demonstrate that the proposed method achieves the same regularized effect as the ordinary dropout algorithm. logic synthesis results show that the proposed method significantly reduces the consumption of FPGA resources in comparison to the ordinary RNG-based approaches.

关键词： Neural networks Dropout field programmable gate array

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Using a Minimum Set of Wearable Sensors to Assess Quality of Movement in Stroke Survivors 17

Using a Minimum Set of Wearable Sensors to Assess Quality of...

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2nd IEEE/ACM international conference on Connected Health - applications, Systems and Engineering Technologies (CHASE)

作者： Sapienza, Stefano Adans-Dester, Catherine O'Brien, Anne Vergara-Diaz, Gloria Lee, Sunghoon Patel, Shyamal Black-Schaffer, Randie Zafonte, Ross Bonato, Paolo Meagher, Claire Hughes, Ann-Marie Burridge, Jane Demarchi, Danilo Harvard Med Sch Dept PM&R 300 First Ave Charlestown MA 02129 USA Univ Southampton Dept Hlth Sci Univ Rd Southampton SO17 1BJ Hants England Politecn Torino Dept Elect & Telecommun Cso Duca Abruzzi 24 I-10129 Turin Italy

ISBN: (纸本)9781509047222

The study herein summarized was focused on the development of a method to derive reliable estimates of the quality of movement of stroke survivors via the analysis of wearable sensor data. Data was collected from 34 subjects while they performed a battery of functional movements that are part of a standard clinical assessment. The quality of movement was assessed using the Functional Ability Scale, a validated clinical scale based on visual observation of movement patterns by a clinical expert. Two wearable sensors were positioned on the stroke-affected wrist and the sternum, respectively. Wearable sensor data was processed to derive data features that were in turn used as input to a regression-based Random Forest algorithm that was trained using a leave-one-subject-out method. The Random Forest algorithm generated estimates of the Functional Ability Scale scores. We found out that the estimates generated via analysis of the wearable sensor data were highly correlated (R-2=0.97) with the scores generated by the clinical expert.

关键词： Estimation field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Adaptive Clinical Data Communication for Remote Monitoring in Rural Ambulance Transport 17

Adaptive Clinical Data Communication for Remote Monitoring i...

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2nd IEEE/ACM international conference on Connected Health - applications, Systems and Engineering Technologies (CHASE)

作者： Hosseini, Mohammad Berlin, Richard R. Jiang, Yu Sha, Lui Univ Illinois Urbana IL 61801 USA Tsinghua Univ Beijing Peoples R China Carle Fdn Hosp Urbana IL USA

ISBN: (纸本)9781509047222

For emergency medical cyber-physical systems, enhancing the safety and effectiveness of patient care, especially in rural ambulance transport, is essential. Use of telecommunication technologies can enhance effectiveness and safety of remote monitoring of patients by the physicians at the center hospital during ambulance transport and provides vital assistance to the emergency medical technicians (EMT) to associate best treatments. However, the communication along the roads in rural areas can range from 4G to 2G to low speed satellite links, with some parts suffering from communication breakage. This unreliable and limited communication bandwidth together with the produced mass of clinical data and the many information exchanges pose a major challenge in real-time and smooth supervision of patients. In this paper, we present parts of developed physiology-aware communication architecture, a bandwidth-compliant criticality-aware system for transmission of clinical data adaptive to varying bandwidths during patient transport. We propose adaptation techniques to transmit more critical data with higher fidelity in response to changes in disease, clinical states, and bandwidth condition. In collaboration with Carle's ambulance service center, we develop a bandwidth profiler, and use it to collect communication traces to support our experiments. Our evaluation results show that our solutions ensure that most critical patient's clinical data are communicated with higher fidelity.

关键词： Estimation field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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A New Cryptography Algorithm to Protect Cloud-based Healthcare Services 17

A New Cryptography Algorithm to Protect Cloud-based Healthca...

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2nd IEEE/ACM international conference on Connected Health - applications, Systems and Engineering Technologies (CHASE)

作者： Aledhari, Mohammed Marhoon, Ali Hamad, Ali Saeed, Fahad Western Michigan Univ Dept Comp Sci Kalamazoo MI 49008 USA Univ Basrah Elect Engn Dept Basrah Iraq Univ Baghdad Informat & Commun Engn Dept Baghdad Iraq

ISBN: (纸本)9781509047222

The revolution of smart devices has a significant and positive impact on the lives of many people, especially in regard to elements of healthcare. In part, this revolution is attributed to technological advances that enable individuals to wear and use medical devices to monitor their health activities, but remotely. Also, these smart, wearable medical devices assist health care providers in monitoring their patients remotely, thereby enabling physicians to respond quickly in the event of emergencies. An ancillary advantage is that health care costs will be reduced, another benefit that, when paired with prompt medical treatment, indicates significant advances in the contemporary management of health care. However, the competition among manufacturers of these medical devices creates a complexity of small and smart wearable devices such as ECG and EMG. This complexity results in other issues such as patient security, privacy, confidentiality, and identity theft. In this paper, we discuss the design and implementation of a hybrid real-time cryptography algorithm to secure lightweight wearable medical devices. The proposed system is based on an emerging innovative technology between the genomic encryptions and the deterministic chaos method to provide a quick and secure cryptography algorithm for real-time health monitoring that permits for threats to patient confidentiality to be addressed. The proposed algorithm also considers the limitations of memory and size of the wearable health devices. The experimental results and the encryption analysis indicate that the proposed algorithm provides a high level of security for the remote health monitoring system.

关键词： Estimation field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Empowering a Gait Feature-Rich Timed-Up-and-Go System for Complex Ecological Environments 17

Empowering a Gait Feature-Rich Timed-Up-and-Go System for Co...

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2nd IEEE/ACM international conference on Connected Health - applications, Systems and Engineering Technologies (CHASE)

作者： Yang, Zhuolin Song, Chen Lin, Feng Langan, Jeanne Xu, Wenyao Univ Buffalo SUNY Dept Comp Sci & Engn Buffalo NY 14260 USA Univ Buffalo SUNY Dept Rehabil Sci Buffalo NY 14214 USA

ISBN: (纸本)9781509047222

Identifying fall risk can prevent injuries in the elderly as well as reduce the related financial burden. A balance assessment, Timed Up and Go (TUG), has been widely applied to estimate fall risk. However, the standardized TUG usually excludes complex factors (e.g. slopes and obstacles) falling short of representing challenges in environments that many older adults navigate. Having information on the motor performance in more complex settings can better inform clinicians about an individual's risk of falling. To this end, we present Smart Insole TUG (SITUG), a cost-efficient, real-time and self-assessment system suitable for the complex environmental TUG. Based on the human stride mechanism, our SITUG educes four refined aspects in the gait feature and segments the TUG process by six detailed phases, providing accurate and advanced information for the fall risk estimation. We evaluate the system with four complex environmental TUG. The results show that the SITUG achieves mean accuracy 94.1% in extracting subcomponents within a stride and 93.13% in deriving the stride length based on the verification of estimated walking distance. Moreover, this system can distinguish six TUG phases with the correctness around 90%.

关键词： Estimation field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Patient Identity Verification based on Physiological Signal Fusion 17

Patient Identity Verification based on Physiological Signal ...

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2nd IEEE/ACM international conference on Connected Health - applications, Systems and Engineering Technologies (CHASE)

作者： Cai, Hang Venkatasubramanian, Krishna K. Worcester Polytech Inst Dept Comp Sci Worcester MA 01609 USA

ISBN: (纸本)9781509047222

Patient identification is crucial in providing proper care in hospitals or other care-facilities. Failure to correctly identify patients can result in a variety of problems such as medication errors, transfusion errors, testing errors, and duplication of EHR records. The current solutions for identifying patients in a hospital setting rely on confirming the patient's identity several times, the use of labels, bar-codes, and RFID tags. However, these solutions are not always sufficient and patient identification errors are common. In this paper we present a patient identity verification approach that can complement existing patient identification solutions in the event that they cannot be relied upon. Our approach works by fusing common physiological signals (vital signs) already collected from the patients. The idea is to fuse two physiological signals electrocardiogram (ECG) with arterial blood pressure (ABP) to identify an individual patient. Existing identification/authentication solutions based on cardiac signals have been primarily tested on healthy patients whose signals exhibit normative rhythm and morphology. However, in our context not all patients can be expected to have normative cardiac signals as many of them may be suffering from ailments that affect the cardiac process. The fusion of multiple ECG and ABP allows us to ensure patient identification even when the patients have ailments that affect their cardiac rhythms. An evaluation of our approach showed that it is over 97% accurate in identifying patients with non-normative cardiac rhythms and morphology with over 99% accuracy for patients whose cardiac rhythms are normative. Further, our approach can identify a patient in as little as 3 seconds, which makes it practical in real-world scenarios.

关键词： Estimation field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Network Optimizations on Prediction Server with Multiple Predictors

Network Optimizations on Prediction Server with Multiple Pre...

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IEEE international conference on Big Data and Cloud Computing (BdCloud)

作者： Kaho Okuyama Yuta Tokusashi Takuma Iwata Mineto Tsukada Kazumasa Kishiki Hiroki Matsutani Dept. of Information and Computer Science Keio University Kohoku Yokohama Japan

ISBN: (纸本)9781728111421;9781728111414

Toward machine learning based prediction services, the prediction server has multiple predictors and selects an appropriate one based on past feedbacks from the clients. In this case, three messages including request, reply, and feedback, are required for each prediction request. Packets are typically transmitted and received via a network protocol stack in OS kernel, and performance improvement can be expected by avoiding the protocol stack since it degrades the communication performance especially for small packets. We implement the prediction server using network optimization approaches including kernel-bypassing and in-NIC processing approaches. Evaluation results show that these network optimizations are beneficial to improve the prediction server performance compared to a baseline prediction server using a standard network protocol stack.

关键词： Servers Optimization Protocols Prediction algorithms Kernel field programmable gate arrays Machine learning

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HADAS and web services: Eco-efficiency assistant and repository use case evaluation

HADAS and web services: Eco-efficiency assistant and reposit...

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international conference in Energy and Sustainability in Small Developing Economies (ES2DE)

作者： Munoz, Daniel-Jesus Pinto, Monica Fuentes, Lidia Univ Malaga Andalucia Tech Malaga Spain

ISBN: (纸本)9781538620663

The interest in "green" Software Engineering, i.e., conscious energy consumption, is relatively recent. Its objective is to make software developers aware of the influence of their design and implementation decisions on the energy consumption of the final product. So far, many experimental results have been published comparing the energy consumption of several alternative solutions, which proven that consumption can be reduced by up to 70%. Although these results are freely available, it is not easy for a developer to apply this knowledge to their applications. Consequently, in this paper we present the HADAS eco-assistant, whose usefulness is: (i) the researchers will store their results in a freely available repository;(ii) developers will be able to reason and get the most energy-efficient configurations that meet their requirements. We will focus on showing the main elements of our proposal and how it applies to real case study of a server machine in a PHP web services development context.

关键词： Estimation field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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A Memory Optimized Mersenne-Twister Random Number Generator 60

A Memory Optimized Mersenne-Twister Random Number Generator

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60th IEEE international Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Saraf, Naman Bazargan, Kia Univ Minnesota Twin Cities Dept Elect & Comp Engn Minneapolis MN 55455 USA

ISBN: (纸本)9781509063895

Random number generators (RNGs) are an integral component of numerous stochastic simulation methods, with applications in diverse scientific disciplines. Recently, stochastic simulation methods are being increasingly implemented on FPGAs for improved performance. Consequently, efficient RNG implementations are essential to successfully realize stochastic simulation methods on FPGAs. We present a memory optimized architecture of the prominent Mersenne-Twister RNG (MT-RNG) for efficient implementation on FPGAs. Our approach leverages the different memory constructs available on an FPGA device to reduce the memory requirements of our architecture by upto 50% over existing designs in published literature. Furthermore, we perform an out-of-order computation of random numbers to reduce the hardware area of our MT-RNG implementation, and compare the hardware metrics of our proposed architecture with the existing implementations on different FPGA platforms.

关键词： field programmable gate arrays (FPGA)

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A Simplified Hybrid EEG-fNIRS Brain-Computer Interface for Motor Task Classification 8

A Simplified Hybrid EEG-fNIRS Brain-Computer Interface for M...

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8th international IEEE/EMBS conference on Neural Engineering (NER)

作者： Zhu, Guangming Li, Rihui Zhang, Tingting Lou, Dandan Wang, Ruirong Zhang, Yingchun Guangdong Prov Work Injury Rehabil Hosp Guangzhou Guangdong Peoples R China Hangzhou Dianzi Univ Hangzhou Zhejiang Peoples R China Univ Houston Dept Biomed Engn Houston TX 77204 USA South China Univ Technol Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781509046034

Hybrid Brain-Computer Interfaces (BCI) has shown great promise for neuro-prosthetics and assistive devices in the field of rehabilitation. However, the complexity involved with the system design and time cost for classification of motor tasks is a core problem when we step into clinical applications. To help address this problem, simultaneous measurements of Electroencephalography (EEG) and functional Near-Infrared Spectroscopy (fNIRS) signals were carried out on three healthy volunteers under a left-right hand grasping paradigm. In this work, we applied a wavelet-based method to extract the wavelet approximation coefficients from EEG signals and we employed the slope information to discriminate the concentration change of Oxygenated hemoglobin (HbO) during left-right hand grasping tasks. To maximize the valuable information implied in two modalities, we proposed an approach based on principle component analysis (PCA) to integrate the features of fNIRS and EEG signals. Two classifiers, including support vector machine (SVM) and linear discriminant analysis (LDA) were applied to identify and estimate the control signals associated with left-right hand grasping tasks. The present experimental result demonstrates that the complement of EEG and fNIRS can significantly improve the classification accuracy with 3 similar to 9% on average. The reduction of dimensionality by PCA could achieve a reduction of time complexity and computational complexity with little loss in accuracy.

关键词： Estimation field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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